Ultra-small Samples Research Articles

Real-time, specific, and label-free transistor-based sensing of organophosphates in liquid

Organophosphates (OP), commonly used in agriculture and as chemical warfare agents, pose significant environmental risks, necessitating real-time, low-cost OP detection methods. In particular, liquid-phase OP sensing with minimal sample volumes is crucial. While several methods allow rapid detection of low concentrations of OP vapors, they are effective only in the short term, while vapors are still being produced. Many OP compounds are semi-volatile, leading to the contamination of water, soil, and surfaces, posing a risk of secondary, long-term exposure. Detecting this contamination requires methods that can be directly applied to droplets of the affected medium. Currently, no method provides the desired combination of ultra-sensitivity, quantitative detection, rapid response, and low-cost for detecting OPs in liquid samples. This study aims to demonstrate quantitative, low-cost, real-time, specific, and label-free OP sensing in ultra-small samples using a transistor-based approach. The current work employs the 2-(4-Aminophenyl)-1,1,1,3,3,3-hexafluoro-2-propanol (aminophenyl-HFIP) functionalized meta-nano-channel field-effect chemical sensor (MNChem sensor) to monitor the organophosphate, diethyl cyanophosphonate (DCNP), in liquid samples. The silicon component of the MNChem is fabricated using a complementary metal-oxide semiconductor (CMOS) process, and the amine-based chemical functionalization of the sensing area is performed post-fabrication. The MNChem sensor provides electrostatic control over the source-drain current (IDS), allowing an optimized channel configuration that efficiently transduces localized OP recognition events into significant IDS variations. Sensing is performed using 0.5 μL buffer solution to simulate a miniature field-deployable sensor for on-site liquid analysis. We report the sensing of DCNP with a limit-of-detection of 100 fg/mL, a dynamic range of 9 orders of magnitude, and excellent linearity (≥0.97) and sensitivity. Control measurements confirm the specificity and reliability of the sensor's response, validating its applicability. This study introduces a novel method for OP detection in contaminated droplets using a low-cost disposable transistor technology.

Method for estimating the number of calibrations of measuring instruments used in production activities

A method for estimating the number of calibrations of measuring instruments used in production activities on the scale of the state economy is proposed and justified. The method is based on the calculation of the so–called calibration weight – the ratio of the annual turnover of the enterprise to the number of calibrations of measuring instruments performed at the enterprise. The number of calibrations of measuring instruments in the industry is calculated as the ratio of the annual turnover of the industry to the weight of calibration in the industry. Similarly, the number of calibrations is calculated for all sectors of the economy of the Russian Federation. As an example of the implementation of the method, the number of calibrations of measuring instruments in the Russian Federation in 2022 was estimated, which amounted to (96±34) million. The validation of the proposed method was carried out, which consisted in comparing the number of verifications of measuring instruments estimated using the proposed method with the number of verifications calculated based on data from FGIS Arshin. As a result, a match was obtained within the limits of the calculation error, which indicates the validity of the proposed method. It is established that the error is due to two main factors: the forced use of ultra-small samples with a volume of less than 10 when estimating the number of calibrations in groups of the All-Russian Classifier of Types of Economic Activity and the spread of values (variance) of the calibration weight in samples with a volume of more than 10. If we assume that the interval between calibrations is comparable to the verification interval, then according to the developed method for estimating the number of calibrations, the volume of the fleet of calibrated measuring instruments in the Russian Federation can be estimated approximately as 150 million units. Thus, for the first time in the Russian Federation, estimates of the number of annual calibrations, as well as the volume of the fleet of calibrated measuring instruments, were obtained. It is advisable to use the obtained results to assess the state of the country's measurement uniformity system, in the strategic planning of the development of the measurement uniformity system.

AI-based tree modeling for multi-point dioxin concentrations in municipal solid waste incineration

Numerous investigations have shown that the municipal solid waste incineration (MSWI) has become one of the major sources of dioxin (DXN) emissions. Currently, the primary issue that needs to be addressed for DXN emission reduction control is the online measurement of DXN. Data-driven AI algorithms enable real-time DXN concentration measurement, facilitating its control. However, researchers mainly focus on building models for DXN emissions at the stack. This approach does not allow for the construction of models that online measurement of DXN generation and absorption throughout the whole process. To achieve optimal pollution control, models that encompass the whole process are necessary, not just models focused on the stack. Therefore, this article focuses on modeling the whole process of DXN concentrations, including generation, adsorption, and emission. It uses machine learning techniques based on advanced tree-based data-driven deep and broad learning algorithms. The determination of data characteristics at different phases is grounded in the understanding of the DXN mechanism, offering a novel framework for DXN modeling. State-of-the-art tree-based models, including adaptive deep forest regression algorithm based on cross layer full connection, tree broad learning system, fuzzy forest regression, and aid modeling technologies, are applied to handle diverse data characteristics. These characteristics encompass high-dimensional small samples, low-dimensional ultra-small size samples, and medium-dimensional small samples across different phases related to DXN. The most interesting is the robust validation where the proposed a whole process tree-based model for DXN is validated using nearly one year of authentic data on DXN generation, adsorption, and emission phases in an MSWI plant of Beijing. The proposed modeling framework can be used to explore the mechanism characterization and support the pollution reduction optimal control.

NAGase sensing in 3% milk: FET-based specific and label-free sensing in ultra-small samples of high ionic strength and high concentration of non-specific proteins

Biosensing with biological field-effect transistors (bioFETs) is a promising technology toward specific, label-free, and multiplexed sensing in ultra-small samples. The current study employs the field-effect meta-nano-channel biosensor (MNC biosensor) for the detection of the enzyme N-acetyl-beta-D-glucosaminidase (NAGase), a biomarker for milk cow infections. The measurements are performed in a 0.5 μL drops of 3% commercial milk spiked with NAGase concentrations in the range of 30.3 aM–3.03 μM (Note that there is no background NAGase concentration in commercial milk). Specific and label-free sensing of NAGase is demonstrated with a limit-of-detection of 30.3 aM, a dynamic range of 11 orders of magnitude and with excellent linearity and sensitivity. Additional two important research outcomes are reported. First, the ionic strength of the examined milk is ∼120 mM which implies a bulk Debye screening length <1 nm. Conventionally, a 1 nm Debye length excludes the possibility of sensing with a recognition layer composed of surface bound anti-NAGase antibodies with a size of ∼10 nm. This apparent contradiction is removed considering the ample literature reporting antibody adsorption in a predominantly surface tilted configuration (side-on, flat-on, etc.). Secondly, milk contains a non-specific background protein concentration of 33 mg/ml, in addition to considerable amounts of micron-size heterogeneous fat structures. The reported sensing was performed without the customarily exercised surface blocking and without washing of the non-specific signal. This suggests that the role of non-specific adsorption to the BioFET sensing signal needs to be further evaluated. Control measurements are reported.

Application of Neural Network Models with Ultra-Small Samples to Optimize the Ultrasonic Consolidation Parameters for 'PEI Adherend/Prepreg (CF-PEI Fabric)/PEI Adherend' Lap Joints.

The aim of this study was to optimize the ultrasonic consolidation (USC) parameters for 'PEI adherend/Prepreg (CF-PEI fabric)/PEI adherend' lap joints. For this purpose, artificial neural network (ANN) simulation was carried out. Two ANNs were trained using an ultra-small data sample, which did not provide acceptable predictive accuracy for the applied simulation methods. To solve this issue, it was proposed to artificially increase the learning sample by including additional data synthesized according to the knowledge and experience of experts. As a result, a relationship between the USC parameters and the functional characteristics of the lap joints was determined. The results of ANN simulation were successfully verified; the developed USC procedures were able to form a laminate with an even regular structure characterized by a minimum number of discontinuities and minimal damage to the consolidated components.

THE PROGRESS OF 14C-AMS ANALYSIS FOR ULTRA-SMALL SAMPLES AT XI’AN AMS CENTER

ABSTRACT As there exists a growing demand for chronological research and tracer applications using radiocarbon (14C) analyses of samples smaller than 100 μg C, a compact micro-specific hydrogen graphitization method has been developed at the Xi’an Accelerator Mass Spectrometry (AMS) Center. This article describes the performance of the system and the mass of carbon background produced during ultra-small sample preparation. Furthermore, we discuss the results of contamination corrections and perform 14C analyses on small samples with known age or reference values. The results reveal that our 14C analysis of ultra-small samples of 10–100 μg C can obtain accurate and reliable results, and the micro-scale 14C-AMS analysis technique meets our research objectives for dating and tracer applications.

Probing the kinetics of chemical reactions in ultra-small droplet samples using digital microfluidic nuclear magnetic resonance spectroscopy

In this study, we present a digital microfluidic (DMF) system that connects analyte droplets with planar microcoils in a high-field nuclear magnetic resonance (NMR) spectrometer for in situ photoreaction analysis. Transparent indium tin oxide glass was employed in fabricating the DMF electrode chips. NMR spectroscopy was utilized for its superior sensitivity and ability to detect small changes in molecular structure, making it highly advantageous for chemical analysis. Utilizing Computer Simulation Technology Studio Suite, we designed a plane annular microstrip coil that accurately matches droplet shape to optimize detection sensitivity and increase filling factor. An advanced DMF control circuit remotely manages droplet samples and facilitates precise mixing for in situ reaction analysis. Our results demonstrate improved sensitivity in the in situ experimental analysis, such as the aldehyde amine reaction (sodium benzaldehyde-2-sulfonate solution and aniline solution) and photopolymerization reaction (polyethylene glycol ester). The integration of DMF and NMR technologies provides a promising approach for increasing efficiency and accuracy in chemical analysis.

Specific and Label‐Free Sensing of Prostate‐Specific Antigen (PSA) from an Ultrasmall Drop of Diluted Human Serum with the Meta‐Nano‐Channel Silicon Field‐Effect Biosensor

AbstractSelf‐use tests are the future of medical diagnostics. Hence, there is a need for low‐cost, simple‐to‐use sensing of multiple analytes from ultrasmall physiological samples. The Meta‐Nano‐Channel (MNC) field‐effect biosensor is employed for sensing of prostate‐specific antigen (PSA). The novelty of the MNC biosensor is: (1) it allows to optimize the coupling between the electrostatics of the biological interactions and the readout current, and (2) it allows to electrostatically affect the biological complexes postinteraction. These attributes yield an optimized and tunable sensing performance. The MNC biosensor is fabricated in a high‐volume silicon chip factory for this research, and an excellent repeatability and robustness in an environment of 1:100 diluted serum is demonstrated. Specific and label‐free PSA sensing is demonstrated from ultrasmall 0.5 µL drops of 1:100 diluted serum with a limit‐of‐detection of 1 fg mL−1, and excellent linearity over a concentration range of six orders of magnitude. Importantly, the attributes of the MNC biosensor allow for a tunable sensitivity and a tunable dynamic range.

Ultra small mass AMS 14C sample preparation and analyses at NIES-TERRA AMS facility

We have made substantial improvements to the NEC 5 MV tandem Pelletron AMS system, such as installing a new type of MC-SNICS ionizer, reconstructing beam lines with the development of the graphite preparation method using an online elemental analyzer for small mass samples down to 1 μgC. To obtain an adequately stable and strong beam current intensity for reliable measurement of small mass samples, we examined graphite position depths (0.35–2.0 mm) related to the optimal geometric conditions to enhance the efficiency of the iron catalyst. Our AMS system generated the most stable and intense beam current at a graphite depth of 1.5–2.0 mm and 2 mg of the iron catalyst, with ionization efficiency of 18–22 %. Under these conditions, the current produced with the 1–10 μgC samples showed a more stable beam current (10–20 μA) and a fivefold increase in beam output duration (greater than 30 min compared to 5 min at 1 μgC). Effects of small carbon graphite-induced isotopic fractionation and higher background was corrected by measuring samples relative to standards of similar mass and a blank. The pMC results were obtained for ultra-small samples ranging from 1 to 50 μgC, calculated relative to adjacent HOxII (NIST SRM 4990C) and IAEA-C1 standards of similar amounts for corrected 14C contents, were approximately in agreement with consensus values overall. By using the method developed in this study, we confirmed the 14C content of ultra-small carbon samples of (1-10 μgC) of IAEA-C8 standards can be measured with precision and accuracy of a few percent.

Multiattention Joint Convolution Feature Representation With Lightweight Transformer for Hyperspectral Image Classification

Hyperspectral image (HSI) classification is currently a hot topic in the field of remote sensing. The goal is to utilize the spectral and spatial information from HSI to accurately identify land covers. Convolution neural network (CNN) is a powerful approach for HSI classification. However, CNN has limited ability to capture non-local information to represent complex features. Recently, vision transformers (ViTs) have gained attention due to their ability to process non-local information. Yet, under the HSI classification scenario with ultra-small sample rates, the spectral-spatial information given to ViTs for global modeling is insufficient, resulting in limited classification capability. Therefore, in this article, Multi-Attention Joint Convolution Feature Representation with Lightweight Transformer (MAR-LWFormer) is proposed, which effectively combines the spectral and spatial features of HSI to achieve efficient classification performance at ultra-small sample rates. Specifically, we use a three-branch network architecture to extract multi-scale convolved 3D-CNN, EMAP, and LBP features of HSI, respectively, by taking full exploitation of ultra-small training samples. Second, we design a series of multi-attention modules to enhance spectral-spatial representation for the three types of features and to improve the coupling and fusion of multiple features. Third, we propose an explicit feature attention tokenizer to transform the feature information, which maximizes the effective spectral-spatial information retained in the flat tokens. Finally, the generated tokens are input to the designed lightweight transformer for encoding and classification. Experimental results on three datasets validate that MAR-LWFormer has an excellent performance in HSI classification at ultra-small sample rates when compared to several state-of-the-art classifiers.

Development of Highly Sensitive Inorganic/Organic Analytical Systems for Ultrasmall Samples Using Atmospheric Pressure Plasmas

Development of Highly Sensitive Inorganic/Organic Analytical Systems for Ultrasmall Samples Using Atmospheric Pressure Plasmas

Femtoliter-Droplet Mass Spectrometry Interface Utilizing Nanofluidics for Ultrasmall and High-Sensitivity Analysis.

In the fields of biology and medicine, comprehensive protein analysis at the single-cell level utilizing mass spectrometry (MS) with pL sample volumes and zmol to amol sensitivity is required. Our group has developed nanofluidic analytical pretreatment methods that exploit nanochannels for downsizing chemical unit operations to fL-pL volumes. In the field of analytical instruments, mass spectrometers have advanced to achieve ultrahigh sensitivity. However, a method to interface between fL-pL pretreatments and mass spectrometers without sample loss and dispersion is still challenging. In this study, we developed an MS interface utilizing nanofluidics to achieve high-sensitivity detection. After charging analyte molecules by an applied voltage through an electrode, the liquid sample was converted to fL droplets by a nanofluidic device. Considering the inertial force that acts on the droplets, the droplets were carried with a controlled trajectory, even in turbulent air flow, and injected into a mass spectrometer with 100% efficiency. A module for heat transfer was designed and constructed, by which all of the injected droplets were vaporized to produce gas-phase ions. The detection of caffeine ions was achieved at a limit of detection of 1.52 amol, which was 290 times higher than a conventional MS interface by electrospray ionization with sample dispersion combined with a similar mass spectrometer. Therefore, sensitivity that was 2 orders of magnitude higher could be realized due to the 100% sample injection rate. The present study provides a new methodology for the analysis of ultrasmall samples with high-sensitivity, such as protein molecules produced from a single cell.

In Situ Microreaction Platform Based on Acoustic Droplet Manipulation for Ultra-High-Precision Multiplex Bioassay.

Liquid droplets rectors have been used in clinical diagnosis, high throughput screening and bioassay. However, it is challenging for droplet reactors to be used in practical applications due to the difficulty of uniformly mixing ultrasmall volumes of samples and the lack of rapid and high-precision detection protocols. Here, we have developed an acoustic droplet system for rapid and efficient biological detection and chemical screening. By employing acoustic wave devices, rapid and nondestructive uniform mixing of ∼nL-μL droplets can be achieved. By the acoustophoretic force, the perturbation of the droplets can quickly concentrate the sample and increase the detection limit by five times. Through the color reaction and the coordinated detection of photodiodes, we have developed a biomarker detection protocol with short reaction time and high accuracy. As a proof-of-concept application, we demonstrated that this system can detect ultrasmall or low-abundance samples faster and more accurately, highlighting its wide application in analytical chemistry, basic research, and clinical medicine.

Optimization of twin parallel microstrips based nuclear magnetic resonance probe for measuring the kinetics in molecular assembly in ultra-small samples.

We present the design, fabrication, characterization, and optimization of a TPM (twin parallel microstrip)-based nuclear magnetic resonance (NMR) probe, produced by using a low-loss Teflon PTFE F4B high frequency circuit board. We use finite element analysis to optimize the radio frequency (RF) homogeneity and sensitivity of the TPM probe jointly for various sample volumes. The RF homogeneity of this TPM planar probe is superior to that of only a single microstrip probe. The optimized TPM probe properties such as RF homogeneity and field strength are characterized experimentally and discussed in detail. By combining this TPM based NMR probe with microfluidic technology, the sample amount required for kinetic study using NMR spectroscopy was minimized. This is important for studying costly samples. The TPM NMR probes provide high sensitivity to analysis of 5 µl samples with 2 mM concentrations within 10min. The miniaturized microfluidic NMR probe plays an important role in realizing down to seconds timescale for kinetic monitoring.

Surfactant-Free Synthesis of Three-Dimensional Perovskite Titania-Based Micron-Scale Motifs Used as Catalytic Supports for the Methanol Oxidation Reaction.

We synthesized and subsequently rationalized the formation of a series of 3D hierarchical metal oxide spherical motifs. Specifically, we varied the chemical composition within a family of ATiO3 (wherein “A” = Ca, Sr, and Ba) perovskites, using a two-step, surfactant-free synthesis procedure to generate structures with average diameters of ~3 microns. In terms of demonstrating the practicality of these perovskite materials, we have explored their use as supports for the methanol oxidation reaction (MOR) as a function of their size, morphology, and chemical composition. The MOR activity of our target systems was found to increase with decreasing ionic radius of the “A” site cation, in order of Pt/CaTiO3 (CTO) > Pt/SrTiO3 (STO) > Pt/BaTiO3 (BTO). With respect to morphology, we observed an MOR enhancement of our 3D spherical motifs, as compared with either ultra-small or cubic control samples. Moreover, the Pt/CTO sample yielded not only improved mass and specific activity values but also a greater stability and durability, as compared with both commercial TiO2 nanoparticle standards and precursor TiO2 templates.

In vitro generation of self-renewing human intestinal epithelia over planar and shaped collagen hydrogels.

The large intestine, with its array of crypts lining the epithelium and diverse luminal contents, regulates homeostasis throughout the body. In vitro crypts formed from primary human intestinal epithelial stem cells on a 3D shaped hydrogel scaffold replicate the functional and architectural features of in vivo crypts. Collagen scaffolding assembly methods are provided, along with the microfabrication and soft lithography protocols necessary to shape these hydrogels to match the dimensions and density of in vivo crypts. In addition, stem-cell scale-up protocols are provided so that even ultrasmall primary samples can be used as starting material. Initially, these cells are seeded as a proliferative monolayer over the shaped scaffold and cultured as stem/proliferative cells to expand them and cover the scaffold surface with the crypt-shaped structures. To convert these immature crypts into fully polarized, functional units with a basal stem cell niche and luminal differentiated cell zone, stable, linear gradients of growth factors are formed across the crypts. This platform supports the formation of chemical gradients across the crypts, including those of growth and differentiation factors, inflammatory compounds, bile and food metabolites and bacterial products. All microfabrication and device assembly steps are expected to take 8 d, with the primary cells cultured for 12 d to form mature in vitro crypts.

Controllable fabrication of pico/femtoliter pipette sampling probes and visual sample volume determination

We propose a hydraulically assisted eddy-current etching method for the controllable fabrication of pico/femtoliter sampling probes with equal inner diameters along the length of the probe. The relative standard deviations of the outer and inner diameters (O.D. and I.D., respectively) of several 1.07-μm-I.D. sampling probe tips fabricated in a single batch using this method were 2.2% and 2.8%, respectively, and the average O.D./I.D. ratio of these probes was 1.17. The probe fabrication method has high reproducibility, and sharp tips are produced, which is advantageous for the transfer of ultra-small sample volumes. Further, the narrow, equal diameter, cylindrical inner bore allows the online, visual determination of the pipetted sample volume by utilizing a microscopic imaging system to measure the liquid length. This value is converted linearly to the pipetted volume, whose measurement error is on a sub-pixel level. Image-based sampling using the fabricated probes was achieved by connecting the probe to an electroosmotic pump, which allowed the controlled pipetting of pico/femtoliter samples. Because the pipette allows samples of the same volume to be measured accurately, the pipette was applied for the semiquantitative mass spectrometry analysis of the metabolites in individual epidermal cells sampled from different parts of Portulaca oleracea plants. The results show that different types of cells have distinct metabolite profiles. Further, the experiments showed that, in dopamine-rich leaves, the content of dopamine in the petioles is higher than that in the foliage. The probe fabrication strategy opens new avenues for the controllable pipetting of ultra-small volume samples and the realization of the visual pipetting of pico/femtoliter samples.

Probing MSC and Tumor Cell Secretome Locally via Dynamic Sampling Platform (DSP)

Background & Aim Within any cell culture, especially on the larger scale of commercial bioreactors, there is considerable heterogeneity that directly impacts the final cell product. This variation results in part from the local shear forces experienced by cells as well as the biochemical microenvironment, e.g., metabolic products and secreted protein factors that can act in a paracrine fashion to modify nearby cells. The ability to measure these critical quality attribute (CQA) biomarkers with high spatial and temporal resolution is foundational to the development of real-time quality monitoring for cell manufacturing. Standard analytical methods quantify neither the local heterogeneity nor the transient nature of cell growth. The Dynamic Sampling Platform (DSP, figure 1) overcomes both barriers by enabling local sampling of the secretome for rapid, high fidelity, and label free CQA identification via inline electrospray ionization mass spectrometry (ESI-MS). Real-time monitoring of the microenvironment with DSP will help predict cell health, viability, and potency, thus enabling the Chemistry, Manufacturing and Controls (CMC) standards for the scale-up and scale-out of cell-based therapies. Methods, Results & Conclusion DSP with ESI-MS sensing enables continuous collection, treatment, and direct infusion of ultra-small samples taken directly from cell culture bioreactors for ESI-MS detection of the cell secretome. DSP-nanoESI-MS is comprised of three elements: 1) a non-invasive sampling interface, which has demonstrated the ability to continuously sample from 2D cell cultures aseptically; 2) a microfabricated mass exchanger for sample treatment which simultaneously removes compounds detrimental to MS analysis, e.g., inorganic salts, and introduces compounds that enhance MS sensitivity; and 3) a spray port for direct infusion nanoESI-MS analysis resulting in identification/fingerprinting of biomolecules in cell cultures. DSP has been applied to multiple live cell cultures to identify differences in the secretome associated with cell state. Analysis of wild type versus interferon gamma primed mesenchymal stromal cells (MSCs) as well as OS-17 and 143-B tumor cell types reveal an enriched ESI-MS signature associated with the different cell types. Localized sampling by DSP is shown to be critical in order to capture higher concentration biomarkers near the cell membrane vs bulk samples that are masked by excessive abundance of biochemical background within the media. The Dynamic Sampling Platform (DSP) samples directly from a cell culture with high spatial resolution to capture critical quality attribute (CQA) biomolecules which indicate the instantaneous cell state and growth trajectory. Rapid, inline sample treatment using the microfabricated mass exchanger removes contaminants, such as inorganic salts, and infuses chemicals that enhance the sensitivity of ESI-MS analysis. Larger CQA biomarkers are selectively retained in the sample channel by the size selective nanomembrane, while smaller contaminants and enhancers transfer across the membrane freely. Real-time electrospray ionization mass spectrometry (ESI-MS) provides detection and identification of broad range of CQA biomolecules with no a priori knowledge of chemical composition.

Method developments for accelerator mass spectrometry at CologneAMS, 53Mn/3He burial dating and ultra-small 14CO2 samples

Abstract Accelerator mass spectrometry (AMS) has a great potential for various geological applications. The precision and sensitivity is directly linked to technical developments. Therefore CologneAMS, the center for accelerator mass spectrometry of the University of Cologne ( Dewald et al., 2013a , Dewald et al., 2013b ), does extensive work on method developments for isotopic ratio measurement, for new applications and to improve the precision. We present two important technical developments: (1) dating of sediments with 53Mn and (2) ultra-small 14CO2 samples. (1) The age determination of discontinuously deposited sediments by measurement of cosmogenic 53Mn and 3He concentration in iron‑titaniumoxides (hematite, magnetite, titanomagnetite, ilmenite), where the measurement of the medium mass isotope 53Mn is difficult because of the interfering isobar 53Cr. It can be measured at only 2 laboratories worldwide. The new AMS system at the Cologne 10 MV FN tandem accelerator is therefore designed especially for the measurement of medium mass isotopes, e.g. 53Mn. It provides the opportunity to use several detector systems in different combinations: degrader foils with an electrostatic analyzer, a 4 m time-of-flight system, a new 135∘ gas-filled magnet, different gas ionization detectors and a projectile x-ray detector. With the implementation of the new 135∘ gas-filled magnet to the 10 MV FN-Tandem accelerator AMS beamline the first tests have shown an increase in transmission and reduction of blank value in comparrison to the measurement with the degrader foil technique (Schiffer et al. 2018). The background level was reduced by a factor of 3.3 and the error normalized sensitivity (Schiffer et al. 2018) was increased by a factor of 1.6. (2) For the measurement of extremely low carbon from cosmogenic in-situ produced 14C or from 14C content of bulk sediments, with 0.01% carbon, technical developments are required to measure low concentrations in terrestrial rocks of 100,000 atoms g−1 in quartz and to trace organic compounds with 10–50 μg of 14CO2 samples. It turned out, that the measurement of 14CO2 micro-samples with the gas-ion source of the Cologne 6 MV AMS system in combination with a gas-handling system is an alternative to the development of a micro-scale graphitization. Modern 1 μg CO2 samples, (14C/12C) = 1.18×10−12, can be measured with this system with a precision of 2.8%. The overall efficiency is 4%–6% and the reproducibility of standard samples is 0.9% with a blank level of 3–6×10−15.

Towards the limits: Analysis of microscale 14C samples using EA-AMS

The coupling of an elemental analyzer (EA) to the gas ion source of an accelerator mass spectrometer (AMS) allows to perform online radiocarbon (14C) analysis of small combustible samples. EA-AMS measurements of small and ultra-small samples containing carbon in the range of 5–100 µg are performed on a routine basis at the MICADAS at ETH Zurich. Samples are encapsulated into vessels prior to combustion in the EA, which introduces extraneous C. The mass and fraction modern (F14C, i.e. the activity ratio of the sample relative to a modern reference material) of this constant contamination was characterized for various vessel materials and shapes. Different vessel cleaning procedures and storage effects were investigated. A minimum contamination mass of 0.10 ± 0.02 µg C per vessel was found for baked Al boats stored in GC-vials. Analysis of standard materials was then performed in order to assess contamination mass and fraction modern of the coupled setup. By applying the model of constant contamination, a mass of 0.44 ± 0.13 µg C and a F14C of 0.48 ± 0.14 were derived. Based on these findings, the mass-dependent detection limit (MDL) was calculated indicating that for a sample containing 5 µg C the F14C has to be superior to 0.03 to make it distinguishable from the background level. Finally, ultra-small samples of three certified reference materials (IAEA C5, C6, C7) were analyzed and corrected according to the model of constant contamination. For all three materials the corrected data was in agreement with the nominal values within the uncertainties.